Stochastic Gene Expression Effects in a Model Retrovirus

描述（由申请人提供）：在本提案中，我们试图对HIV-1慢病毒模型中的基因表达动力学进行严格的实验和计算分析。慢病毒系统来源于HIV-1，但保留了Tat介导的控制转录活性的正反馈环。这种反馈环基序是所有生物体和细胞子系统中共同的基因调控结构，因此从本研究中得出的测量和结论将广泛适用。基于物理化学原理和系统的简单模型，我们假设（并显示了最初的实验结果），来自该系统的基因表达是高度随机的，并且Tat介导的反馈被零星地激活，使得在病毒感染其靶细胞并整合到宿主基因组中之后，在病毒表达达到可以发生繁殖然后传播的点之前，可能经过了相当长的一段时间。这段时间可能足以让激活的T细胞转变到其记忆状态，从而将慢病毒捕获在非活性形式，直到记忆细胞被重新激活。因此，这是可能的，这种假设的噪音是足够大，以有助于形成的潜伏池的病毒，使HIV-1很难治疗。然而，有这种可能性的实验证据很少，而且它从来没有严格表明，哺乳动物的基因表达是显着的随机性。因此，我们提出了一个程序，用于定量测量在这个慢病毒，HIV-1为基础的，自动激活的基因表达系统的关键步骤的积分点依赖的动力学。我们使用专门设计的病毒结构与荧光标记的表达和定量显微镜技术梳理出的真核基因表达模型的模型的所有参数。我们使用这些模型来估计从整合点到转录起始、到tar的延伸控制、到达特产生/降解、到达特/tar相互作用在表达过程中产生噪声并允许延迟直到病毒产生的过程中每个步骤的作用。我们还使用模型与数据的比较来确定哪些参数不受优化的约束，从而直接测量。由此产生的实验验证模型的哺乳动物病毒基因表达将是一个资源，其他研究动力学和噪声在真核细胞过程中的作用。

DESCRIPTION (provided by applicant): In this proposal we seek to perform a rigorous experimental and computational analysis of the dynamics of gene expression in a lentiviral model of HIV-1. The lentiviral system is derived from HIV-1 but leaves the Tat-mediated positive feedback loop controlling transcriptional activity intact. This feedback loop motif is a common gene regulatory architecture across all organisms and cellular subsystems thus measurements and conclusions derived from this study will apply broadly. Based on physical chemical principles and simple models of the system, we hypothesize (and show initial experimental results) that gene expression from this system is highly stochastic and that the Tat-mediated feedback is activated sporadically such that after the virus infects its target cell and integrates into the host genome, there may be significant periods of time elapsed before viral expression reaches the point where reproduction can occur and then propagate. This time could be enough to allow an activated T-cell to transition to its memory state thereby trapping the lentivirus in an inactive form until such time as that memory cell is reactivated. Thus, it is possible that this hypothesized noise is large enough to contribute to the formation of the latent pool of virus that makes HIV-1 so hard to treat. However, there is little experimental evidence of this possibility and further it has never been rigorously shown that mammalian gene expression is significantly stochastic. We therefore set out a program for quantitatively measuring the integration-point dependent kinetics of the key steps in this lentiviral, HIV-1 based, autoactivated gene expression system. We use specially designed viral constructs with fluorescent markers of expression and quantitative microscopy techniques to tease out all the parameters for a model of the eukaryotic gene expression model. We use the models to estimate the role of each of the steps in the process from integration point, to transcription initiation, to elongation control by tar, to Tat production/ degradation, to Tat/tar interaction in generating noise in the expression process and allowing delays until viral production. We also use the comparison of models to data to determine which parameters are not constrained by optimizations and thus direct measurements. The resultant experimentally-validated model of mammalian viral gene expression will be a resource for others studying the kinetics and role of noise in eukaryotic cellular processes.